Re: st: AW: double hurdle model with Tobit second stage estimation

I do not seem to get the paper in The Stata Journal. Actually I have no
access to the journal. However, if I get you correctly do I estimate a
probit model of the first stage then before estimating the tobit model I
write " drop if <var> == 0 ", then estimate the Tobit directly? Will
this solve my problem whereas the Tobit model does not account for the
joint correlation of the error terms in the two models?

For your information the dependent variable in the second stage is a
continuous variable with 70% pile up of zeros not count.

Saha et. al, 1997 ( Applied Economics, 1997, 29, 1311-1316) in their
paper on "Calculating Marginal effects for zero expenditures ....."
argue that the problem can be solved by adding inverse of the Mills
Ration of the first stage Probit. This is equivalent to the two stage
Heckman selection model which I am not sure solves my problem.

I am wondering which would help?
Kirimi
Erickson, Ken wrote:

Hi David and 'Statalisters',
My colleague Mike just suggested this:
...Ken,
Can you send my response to him?
You need to use a drop statement drop if <var> == 0
Do this before the second stage...
See "From the help desk: hurdle models," The Stata Journal, 2003, 3, Number 2, pp.178-184.
Hope this helps!
Ken Erickson
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of David Jacobs
Sent: Wednesday, February 25, 2009 1:47 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: AW: double hurdle model with Tobit second stage estimation

You've probably thought of this as well, but what
about the -zip- or -znb- models in Stata. Those
options allow large proportions of zeros in your outcome variable.

Is the problem with these models that the values
above zero are not integers? If they are
integers or could be made into integers without
messing things up, then these two equation count estimators might work.

Dave Jacobs
At 01:16 PM 2/25/2009, you wrote:

Heckprob is not appropriate in my case. Heckprob
would treat the pile of zeros i have as
unobserved whereas the Tobit treats them as
observed zeros. This is the case in my data and
therefore heckprob is not an appropriate model.
I could run a first stage Probit then a second
stage Tobit. However, the Tobit in the second
stage does not use all the data observed and
hence the standard errors will not be correct
leading to wrong t statistics and be unable to interpret the results.

I working on a double hurdle model. The first
stage is a Probit model and the second stage is
Tobit due to pile up of zeros. Is there a do
program that can assist me in this procedure to
get the correct standard errors accounting for the first stage estimation?

Thank you,
Kirimi

--
*******************************

Imagination is more important than knowledge.
For while knowledge defines all we currently
know and understand, imagination points to all
we might yet discover and create.